Figure 1.

Distinctive patterns of miRNA expression between cervical cancer and normal samples
revealed by principal component analysis. microRNA incidence values from each sample were projected onto the first two principal
components, using cube-rooted data. This two-dimensional representation of the ~714
dimensional primary data resulted in evident separation between normal and tumour
samples but not between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) samples.
The first principal component explains 21.2% of the variation present in the data
and the second explains 11.6%. ASC, adenosquamous cell carcinoma; T, tumour; N, normal.